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Bots and gender profiling on twitter using sociolinguistic features notebook for PAN at CLEF 2019

dc.contributor.advisor
dc.contributor.editorCappellato L.
dc.contributor.editorFerro N.
dc.contributor.editorLosada D.E.
dc.contributor.editorMuller H.
dc.creatorPuertas E.
dc.creatorMoreno-Sandoval L.G.
dc.creatorPlaza-Del-Arco F.M.
dc.creatorAlvarado-Valencia J.A.
dc.creatorPomares-Quimbaya A.
dc.creatorAlfonso Ureña-López L.
dc.date.accessioned2020-03-26T16:33:10Z
dc.date.available2020-03-26T16:33:10Z
dc.date.issued2019
dc.identifier.citationCEUR Workshop Proceedings; Vol. 2380
dc.identifier.issn16130073
dc.identifier.urihttps://hdl.handle.net/20.500.12585/9191
dc.description.abstractUnfortunately, in social networks, software bots or just bots are becoming more and more common because malicious people have seen their usefulness to spread false messages, spread rumors and even manipulate public opinion. Even though the text generated by users in social networks is a rich source of information that can be used to identify different aspects of its authors, not being able to recognize which users are truly humans and which are not, is a big drawback. In this work, we describe the properties of our multilingual classification model submitted for PAN2019 that is able to recognize bots from humans, and females from males. This solution extracted 18 features from the user's posts and applying a machine learning algorithm obtained good performance results. © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).eng
dc.format.mediumRecurso electrónico
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherCEUR-WS
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourcehttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85070510020&partnerID=40&md5=fcc69ef587023e644e71d9b5f6e5be01
dc.titleBots and gender profiling on twitter using sociolinguistic features notebook for PAN at CLEF 2019
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datacite.rightshttp://purl.org/coar/access_right/c_16ec
oaire.resourceTypehttp://purl.org/coar/resource_type/c_c94f
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
dc.source.event20th Working Notes of CLEF Conference and Labs of the Evaluation Forum, CLEF 2019
dc.type.driverinfo:eu-repo/semantics/conferenceObject
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.subject.keywordsAuthor profiling
dc.subject.keywordsBots profiling
dc.subject.keywordsComputational linguistic
dc.subject.keywordsGender profiling
dc.subject.keywordsSociolinguistic
dc.subject.keywordsUser profiling
dc.subject.keywordsCharacter recognition
dc.subject.keywordsClassification (of information)
dc.subject.keywordsComputational linguistics
dc.subject.keywordsLearning algorithms
dc.subject.keywordsLinguistics
dc.subject.keywordsMachine learning
dc.subject.keywordsSocial aspects
dc.subject.keywordsSocial networking (online)
dc.subject.keywordsSocial sciences computing
dc.subject.keywordsAuthor profiling
dc.subject.keywordsBots profiling
dc.subject.keywordsGender profiling
dc.subject.keywordsSociolinguistic
dc.subject.keywordsUser profiling
dc.subject.keywordsBotnet
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccess
dc.rights.ccAtribución-NoComercial 4.0 Internacional
dc.identifier.instnameUniversidad Tecnológica de Bolívar
dc.identifier.reponameRepositorio UTB
dc.relation.conferencedate9 September 2019 through 12 September 2019
dc.type.spaConferencia
dc.identifier.orcid57202285682
dc.identifier.orcid57194828933
dc.identifier.orcid57191078469
dc.identifier.orcid8738428200
dc.identifier.orcid57203852380
dc.identifier.orcid56986551200


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